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Publication Detail
Previous, current, and future stereotactic EEG techniques for localising epileptic foci
  • Publication Type:
    Journal article
  • Authors:
    Dasgupta D, Miserocchi A, McEvoy AW, Duncan JS
  • Publisher:
    Informa UK Limited
  • Publication date:
    24/08/2022
  • Journal:
    Expert Review of Medical Devices
  • Medium:
    Print-Electronic
  • Status:
    Accepted
  • Country:
    England
  • Print ISSN:
    1743-4440
  • Language:
    English
  • Keywords:
    Intracranial EEG, computer-assisted planning, drug resistant focal epilepsy, epilepsy surgery, neuronavigation, robot-assisted surgery, stereo-EEG, surgical planning
  • Notes:
    © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Abstract
INTRODUCTION: Drug-resistant focal epilepsy presents a significant morbidity burden globally, and epilepsy surgery has been shown to be an effective treatment modality. Therefore, accurate identification of the epileptogenic zone for surgery is crucial, and in those with unclear noninvasive data, stereoencephalography is required. AREAS COVERED: This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally. EXPERT OPINION: We provide a perspective on the future directions in the field, reviewing improvements in predicting electrode bending, image acquisition, machine learning and artificial intelligence, advances in surgical planning and visualization software and hardware. We also see the development of EEG analysis tools based on machine learning algorithms that are likely to work synergistically with neurophysiology experts and improve the efficiency of EEG and SEEG analysis and 3D visualization. Improving computer-assisted planning to minimize manual input from the surgeon, and seamless integration into an ergonomic and adaptive operating theater, incorporating hybrid microscopes, virtual and augmented reality is likely to be a significant area of improvement in the near future.
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